Google Cloud Certification: Cloud Data Engineer Professional Certificate
Investigate the objectives and advantages of Google's Big Data and Machine Learning products, including the use of BigQuery for interactive analysis, Cloud SQL, and Dataproc for migrating MySQL and Hadoop applications, and the selection of a variety of data processing tools on Google Cloud.
Description for Google Cloud Certification: Cloud Data Engineer Professional Certificate
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by Google Cloud
Duration: 1 month at 10 hours a week
Schedule: Flexible
Pricing for Google Cloud Certification: Cloud Data Engineer Professional Certificate
Use Cases for Google Cloud Certification: Cloud Data Engineer Professional Certificate
FAQs for Google Cloud Certification: Cloud Data Engineer Professional Certificate
Reviews for Google Cloud Certification: Cloud Data Engineer Professional Certificate
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Google Cloud Certification: Cloud Data Engineer Professional Certificate
Begin your vocation in generative AI data engineering. Obtain the necessary skills to secure a position as a data engineer by acquiring an understanding of generative AI. No prior experience is required.
This learning path provides a thorough overview of generative AI. This specialization delves into the ethical considerations that are essential for the responsible development and deployment of AI, as well as the foundations of large language models (LLMs) and their diverse applications.
Learn machine learning with Google Cloud. End-to-end machine learning experimentation in the real world
Learn how to use Gemini for Google Workspace to boost productivity and efficiency in Gmail through its generative AI features.
Learn to build machine learning solutions using Generative AI on AWS, including an understanding of AWS cloud computing and utilizing services like Amazon Bedrock.
Acquire the skills necessary to program powerful systems in Rust. Through projects in data engineering, Linux tools, DevOps, LLMs, Cloud Computing, and machine learning operations, acquire the skills necessary to develop software that is both efficient and robust, utilizing Rust's distinctive safety and speed.
Become an adept in the field of machine learning. Break into the field of artificial intelligence by mastering the fundamentals of deep learning. Recently upgraded with state-of-the-art methodologies!
Gain the skills needed for a machine learning engineering role and prepare for the Google Cloud Professional Machine Learning Engineer certification exam by learning to design, build, and productize ML models using Google Cloud technologies.
Gain practical experience in optimizing, deploying, and scaling machine learning models using Google Cloud Platform through a structured five-course specialization with hands-on labs and a focus on advanced topics and recommendation systems.
Become a machine learning engineer. Enhance your programming abilities with MLOps
Featured Tools
The specialization caters to machine learning professionals seeking TensorFlow skills through a structured progression from basics to advanced topics, emphasizing practical application through capstone projects.
Discover how to use Rust to apply DevOps ideas, automate system chores, and put logging and monitoring in place for effective application deployment and operation.
Learn to use Generative AI for creating compelling logos and establishing a strong brand identity that fosters customer loyalty.
By utilizing modern Python libraries, investigating machine learning tools, and delving into logistic regression, decision trees, and linearly inseparable data, you can master AI with our course.
Learn about various generative AI models and architectures, the application of LLMs in language processing, and implement NLP preprocessing techniques using libraries and PyTorch.